동적 신경망에 의한 로봇 좌표 변환의 역기구학적 학습

Inverse Kinematic Learning of Robot Coordinate Transformations Using Dynamic Neural Network

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are provided to demonstrate the effectiveness of the proposed learning using the DNP.